Emerging Technology
Emerging technology refers to the new technology and innovations in different areas such as media, business, science, and education. But it may also refer to the continuing development of existing technology.
Artificial Intelligence (AI)
AI is a branch of computer science that deals with building machines capable of solving complex problems which require human intelligence. AI can be referred to as the simulation of human intelligence by machines. The father of AI, John McCathy a professor of computer science at Stanford coined the term “Artificial Intelligence” in 1956.
Characteristics of AI
- The ability to act intelligently as a human.
- The ability to behave following “general intelligent action”.
- The ability to artificially simulate the human brain.
- The ability to actively learn and adapt as a human.
- The ability to process language and symbols.
Application of AI
A IOT of technological development has been achieved in AI today. Because of its feature, AI has its application in many areas such as:
- Entertainment:
Some of the popular online streaming platforms such as Netflix and Amazon Prime uses AI and machine learning algorithms to study user’s behaviour based on his/her engagement to suggest videos. - Robotics:
One of the major applications of AI is robotics. Robots are programmed to perform some task repeatedly. But with the integration of AI Robots have become intelligent and can monitor, analyse, learn, and improve without any human intervention. - Gaming:
Another sector where AI is used extensively is gaming. The games make use of AI for decision-making and simulation of human behaviour and can also predict human behaviour. In 2014, a game called “Alien Isolation” was developed. It uses AI to stalk the player throughout the game. - Healthcare:
One of the vital applications of AI can be seen in the healthcare industry. With AI experts systems are built that can diagnose critical disease. The AI-based systems are capable of identifying cancer cells. For research and discovery of new drugs also AI based system are used. - Social media:
The social media platform such as Facebook, Instagram, Twitter, Tik Tok, etc. use all of various purposes. Facebook and Instagram use AI tool called the Deep Text to monitor comments and posts. They also use AI to display ads based on your engagement.
Cloud computing and Distributed computing
Cloud computing refers to the delivery of computing services—such as storage, databases, networking, software, and moreover, the internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale. Cloud computing services are typically categorized into three main types:
i) Infrastructure as a Service (IaaS):
Provides virtualized computing resources over the internet. Users can rent virtual machines, storage, and networking resources on a pay-as-you-go basis.
IaaS services:
Computing infrastructure, physical or virtual machines, networking, storage, networking service, etc.
- ii) Platform as a Service (PaaS): Offers a platform allowing customers to develop, run, and manage applications without dealing with infrastructure management. PaaS providers offer tools and services to streamline application development and deployment.
PaaS services:
Computing platforms which typically include OS programming language execution environment, Runtimes, database, web server etc.
iii) Software as a Service (SaaS):
Delivers software applications over the internet on a subscription basis. Users can access these applications through a web browser without needing to install or maintain the software locally.
SaaS services:
Google Apps, Microsoft office 365, Cisco WebEx, Salesforce, Workday, Concur, Citrix GoTo metting Application like Email, social networking sites.
Advantage of cloud computing
Certainly! Let’s delve into each of these advantages of cloud computing:
Reduced Cost:
Cloud computing can significantly reduce costs compared to traditional IT infrastructure. With cloud services, businesses can avoid upfront capital expenditures on hardware and data centers. Instead, they pay for computing resources on a pay-as-you-go or subscription basis, which often results in lower overall expenses.
Storage Service:
Cloud computing offers scalable storage solutions that can adapt to the changing needs of businesses. Cloud storage services provide virtually unlimited capacity, allowing organizations to store vast amounts of data without worrying about physical storage constraints.
Reliability:
Cloud computing platforms are built with redundancy and fault tolerance, which enhances reliability and uptime. Cloud service providers operate data centers across multiple geographic regions, minimizing the risk of downtime due to hardware failures or natural disasters.
Security:
While security concerns are often cited as a barrier to cloud adoption, reputable cloud providers invest heavily in security measures to protect customer data. Cloud computing offers several security advantages, including robust encryption mechanisms, identity and access management controls, and regular security audits and compliance certifications.
Distribution computing:
It refers to the technique of linking multiple computers together in order to share data and coordinate processing power.
Advantage of Distributing computing
Distributed computing, which involves breaking down computational tasks and distributing them across multiple interconnected computers, offers several advantages, including:
Scalability:
Distributed computing architectures can easily scale to handle growing workloads by adding more computing nodes or resources. This scalability allows systems to accommodate increased demand without experiencing performance degradation or downtime.
Improved Performance:
Distributing computational tasks across multiple nodes can lead to improved performance compared to centralized systems. Parallel processing techniques enable distributed computing systems to execute tasks concurrently, reducing processing time and improving overall system throughput.
Cost-Effectiveness:
Distributed computing can be cost-effective compared to traditional monolithic architectures. By leveraging commodity hardware and open-source software, organizations can build distributed systems at a lower cost without sacrificing performance or scalability.
Reliability:
Distributed computing architectures are inherently more resilient and fault-tolerant than centralized systems. By distributing computational tasks across multiple nodes, distributed systems can withstand individual node failures without experiencing service interruptions or data loss.
IoT
The Internet of Things (IoT) refers to the network of interconnected devices that communicate and exchange data with each other over the internet.
Key components of the IoT ecosystem include:
Devices:
IoT devices come in various forms, including sensors, actuators, wearables, vehicles, appliances, and industrial machines. These devices collect data from their surroundings or perform specific actions based on received instructions.
Connectivity:
IoT devices rely on various communication technologies to connect to the internet and transmit data. These technologies include Wi-Fi, Bluetooth, Zigbee, cellular networks (3G/4G/5G), LPWAN (Low-Power Wide-Area Network), and satellite communication.
Data Processing and Analytics:
The data collected by IoT devices is processed and analyzed to extract valuable insights and make informed decisions. This involves techniques such as real-time stream processing, data mining, machine learning, and artificial intelligence.
User Interface
The user interface (UI) enables users to interact with IoT systems, visualize data, and control connected devices. UI components may include : Web Dashboards, Mobile Applications, Command-Line Interfaces (CLIs), Voice Interfaces.
Advantage of IOT
- Efficiency and Automation
- Data-driven Insights
- Improved Decision-making
- Enhanced Customer Experience
- Cost Savings
- Remote Monitoring and Management
- Safety and Security
- Sustainability
Big data
Big data refers to large and complex data sets that are difficult to process using traditional database management tools or traditional data processing applications.
Big data sources:
- Social Media
- Stock Exchange
- Weather Forecast
- E-Commerce
- Bank/Credit Card transaction
- Scientific instruments
- Mobile devices etc.
Characteristics of Big data
- Volume:
Volume refers to the amount of data. The size of data plays a very crucial role in determining whether a particular data can actually be considered as Big data or not. - Variety:
Variety refers to different types of data. The sources and the nature of data are not only structured today but mostly the source are unstructured and semi-structured. - Velocity:
Velocity refers to the speed to the speed of generation of data. How fast the data generated and processed to meet the demands, determines the real potential in the data. - Variability:
This refers to the inconsistency in the data, thus hampering the process of being able to handle and manage the data effectively.
Data Mining
Data mining is the process of extracting usable data, and valuable information from large data sets. With data mining, a business can find customer behaviours which are impossible to discover with human analysis.
Advantage of data mining
Better Marketing:
Data mining enables businesses to analyze large datasets to identify patterns, trends, and insights related to customer behavior, preferences, and demographics. This information allows marketers to develop more targeted and personalized marketing campaigns, resulting in better engagement, higher conversion rates, and improved ROI.
Improved Customer Relationship:
Data mining helps businesses gain deeper insights into customer needs, preferences, and satisfaction levels. By analyzing customer interactions, feedback, and purchase history, organizations can identify opportunities to enhance customer experiences, address issues proactively, and build stronger relationships.
Increased Cost Efficiency:
Data mining can help businesses identify inefficiencies, optimize processes, and reduce operational costs. By analyzing operational data, organizations can identify areas for improvement, streamline workflows, and eliminate waste. For example, data mining techniques such as predictive analytics can help businesses forecast demand, optimize inventory levels, and reduce carrying costs. Additionally, data mining can identify fraudulent activities, leading to cost savings through fraud detection and prevention.
Enhanced Employee Productivity:
Data mining provides valuable insights that can empower employees to make better decisions and perform their jobs more effectively. By providing access to relevant data and analytics tools, organizations can enable employees to identify opportunities, solve problems, and optimize performance.
Application areas of data mining
E-commerce:
Data mining plays a crucial role in e-commerce by helping businesses understand customer behavior, preferences, and purchase patterns. Retailers use data mining techniques such as market basket analysis to identify product associations and recommend complementary items to customers.
Insurance:
In the insurance industry, data mining is used for risk assessment, fraud detection, and customer retention. Insurers analyze historical claims data and customer profiles to assess risk factors and determine insurance premiums accurately. Data mining techniques such as predictive modeling identify fraudulent claims by detecting suspicious patterns and anomalies in claim submissions.
Entertainment:
Data mining enhances the entertainment industry by enabling content recommendation, audience segmentation, and predictive analytics. Streaming platforms use collaborative filtering algorithms to analyze user interactions and preferences, recommending personalized content based on viewing history and ratings.
Healthcare:
Data mining transforms healthcare delivery by enabling clinical decision support, disease prediction, and patient management. Healthcare providers analyze electronic health records (EHRs), medical imaging data, and genomic information to identify disease patterns, risk factors, and treatment outcomes. Predictive modeling identifies patients at high risk of developing chronic conditions or experiencing adverse events, enabling early intervention and preventive care strategies.
Banks:
Data mining revolutionizes banking operations by facilitating customer segmentation, credit scoring, and fraud detection. Banks analyze transaction data, credit histories, and customer demographics to segment customers into distinct groups based on their financial needs and behaviors. Predictive analytics assesses creditworthiness and assigns credit scores to loan applicants, enabling banks to make informed lending decisions and manage credit risk effectively.
Cryptography
Cryptography is the practice and study of techniques for secure communication and data protection in the presence of adversaries. It involves encoding plaintext data into ciphertext using cryptographic algorithms and keys to ensure confidentiality, integrity, authentication, and non-repudiation.Key concepts and components of cryptography include:
Encryption:
Encryption is the process of converting plaintext data into ciphertext using cryptographic algorithms and keys. The ciphertext is unreadable without the corresponding decryption key, ensuring confidentiality.
Decryption:
Decryption is the reverse process of encryption, where ciphertext is converted back into plaintext using the decryption key. Only authorized parties with the correct decryption key can decipher the encrypted data.
Types of cryptography
Here are some common types of cryptography:
Symmetric Cryptography:
In symmetric cryptography, the same key is used for both encryption and decryption of data. This means that the sender and receiver must both possess the same secret key to communicate securely.
Asymmetric Cryptography:
Asymmetric cryptography uses a pair of keys—a public key and a private key—for encryption and decryption, respectively. The public key is widely distributed and can be freely shared, while the private key is kept secret.
Virtual Reality
Virtual Reality (VR) refers to a simulated experience that immerses users in a computer-generated environment, typically through the use of specialized hardware such as VR headsets or goggles. In a VR environment, users can interact with and explore virtual worlds in a way that simulates physical presence and sensory experiences.Virtual reality has diverse applications across various industries and domains, including gaming, entertainment, education, healthcare, architecture, engineering, training, simulation, and telepresence. VR technology has the potential to transform how we interact with digital content, learn new skills, collaborate with others, and experience immersive storytelling and entertainment.
Augmented Reality
Augmented Reality (AR) is a technology that overlays digital information, such as images, videos, or 3D models, onto the real-world environment, thus enhancing or “augmenting” the user’s perception of reality. Unlike virtual reality (VR), which immerses users in entirely simulated environments, AR blends digital content with the physical world, allowing users to interact with both simultaneously. Augmented reality has diverse applications across various industries and domains, including gaming, education, retail, healthcare, architecture, manufacturing, marketing, and navigation. AR technology enables interactive product visualization, immersive learning experiences, remote assistance, location-based information overlays, and innovative marketing campaigns.
Different between VR and AR
| VR | AR |
| VR creates an immersive virtual environment. | AR combines real and virtual world. |
| Its hardware to distinguish between real and virtual world. | It is possible to distinguish real and virtual world. |
| VR is 75% virtual and 25 % real. | AR is 25% virtual and 75% real. |
| VR headset device is required. | Headsets not required. |
| It is mostly used for games and training. | It is mostly used for demonstrating. |
| The user are completely immersed in a fictional world and are isolated from the real world. | The users are still in touch with the real world while interacting with virtual objects. |